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by dogma1138 3622 days ago
If you have a 40 PCIE lane CPU (and not NVME drives) was the price the thing that actually held you back? The scaling past 2 cards is also pretty horrible, depending on how much of a performance increase it would most likely still be cheaper to get 2 new Titan X's instead of upgrading your maxwell cards if you can offload them at 400-500$.
1 comments
akiselev 3622 days ago
It would probably be pretty useless for gaming over 2x or 3x SLI but depending on whether any CUDA work you need to do is compute or memory (not bandwidth) bound, it can still make a difference worth the cost.
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dogma1138 3622 days ago
Well SLI has nothing to do with CUDA, you can have as many CUDA supported cards as you want and use all of them they don't even have to be from the same model/generation and you can use them all. Since he mentioned SLI i assumed it was for gaming since it's the only thing that actually limits you. But that said the number of PCIE lanes is still a problem this is why people that do work on compute opt out (well are forced to) use Xeon parts with QPI to get enough PCIE lanes because the amount of lanes available for standard desktop parts (including the PCH) is pretty pathetic even if you are going with the full 40 PCIE lanes E series of CPU's. This can be even worse if you want to use SATA Express or NVME drives since they also use your PCIe lanes, as well as a few other things like M.2 wireless network cards (pretty common these days on the upper midrange and high end motherboards), Thunderbolt and a few other things.
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akiselev 3622 days ago
To repeat what I just said woth slightly different wording: Yes, my point was specifically referring to the difference between users who want the Titan X for supercomputing versus those who want it for gaming. You can have as many CUDA cards as you want but you face the same problem of limited PCIe bandwidth just like you do with gamers who want SLI. If your use case is CUDA and not gaming, then the usefulness of four Titans depends entirely on whether your algorithms are limited by memory, memory bandwidth, or computing power.
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